'''SmartCarving''' is a [[File Carving|file carving]] technique to recover fragmented files first proposed by [[User:PashaPal|A. Pal]] and N. Memon in DFRWS 2008. SmartCarving utilizes a combination of structure based validation along with validation of each file's unique content. Results for the SmartCarving technique

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'''SmartCarving''' is a [[File Carving|file carving]] technique to recover fragmented files first proposed by [[User:PashaPal|A. Pal]] and [[User:NasirMemon|N. Memon]] in DFRWS 2008. SmartCarving utilizes a combination of structure based validation along with validation of each file's unique content. Results for the SmartCarving technique

were demonstrated on fragmented jpegs in the DFRWS 2006 and DFRWS 2007 challenges. From these two challenges SmartCarving was able

were demonstrated on fragmented jpegs in the DFRWS 2006 and DFRWS 2007 challenges. From these two challenges SmartCarving was able

to recover all but one fragmented jpeg file.

to recover all but one fragmented jpeg file.

==History==

==History==

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Memon et al.[1] presented an efficient algorithm based on a greedy heuristic and alpha-beta pruning for reassembling fragmented images.

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[[User:NasirMemon|Memon]] et al.[1] presented an efficient algorithm based on a greedy heuristic and alpha-beta pruning for reassembling fragmented images.

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Building on this work, Memon et al.[2] researched and introduced sequential hypothesis testing as a an effective mechanism for detecting fragmentation points of file. This paper won the best paper award for DFRWS 2008. The techniques presented in the paper were the foundation for the overall SmartCarving design.

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Building on this work, [[User:NasirMemon|Memon]] et al.[2] researched and introduced sequential hypothesis testing as a an effective mechanism for detecting fragmentation points of file. This paper won the best paper award for DFRWS 2008. The techniques presented in the paper were the foundation for the overall SmartCarving design.

==Details==

==Details==

Revision as of 03:03, 27 October 2009

SmartCarving is a file carving technique to recover fragmented files first proposed by A. Pal and N. Memon in DFRWS 2008. SmartCarving utilizes a combination of structure based validation along with validation of each file's unique content. Results for the SmartCarving technique
were demonstrated on fragmented jpegs in the DFRWS 2006 and DFRWS 2007 challenges. From these two challenges SmartCarving was able
to recover all but one fragmented jpeg file.

Contents

History

Memon et al.[1] presented an efficient algorithm based on a greedy heuristic and alpha-beta pruning for reassembling fragmented images.
Building on this work, Memon et al.[2] researched and introduced sequential hypothesis testing as a an effective mechanism for detecting fragmentation points of file. This paper won the best paper award for DFRWS 2008. The techniques presented in the paper were the foundation for the overall SmartCarving design.

Details

After identifying a header block of a specific file type, for example, jpeg, a SmartCarver will analyze each subsequent block to determine if it
belongs or does not belong to the starting block. If a block is determined not to belong, then the file is assumed to be fragmented and the
SmartCarving algorithm looks for the next fragment by matching the data of other available blocks with the first fragment. This process can be
done in parallel for many files.

Applications

There are currently two applications available that utilize SmartCarving, both produced by Digital Assembly: